Project Summary/Abstract Although hypotheses have been advanced concerning the role of structural brain maturation as determinants of changes in neural function, specific morphophysiologic correlations and their developmental trajectories have not been experimentally validated. Our previous multimodal brain imaging studies examining young children and adolescents provide evidence that brain development involves straightforward brain structure-function mechanistic relations. Given that whole-head infant MEG and high-resolution multi-band diffusion and structural MRI are now available, we are at an important time in the history of developmental neurobiology and imaging, ideally positioned to begin developing, testing, and refining models of brain structure-function relations. In addition to understanding brain structure-function associations, a primary goal is the identification of infant brain measures that best predict future brain function (and behavior) and thus the identification of prognostic brain biomarkers for future studies. The above is accomplished via a dense longitudinal design (5 points over 12months) and the use of passive MEG tasks that allow assessment of brain activity in infants. Primary sensory areas are targeted as it is through the maturation of primary sensory regions (not frontal lobes) that infants first experience the world. The neural signal correlates assessed are selected as these measures indicate how rapidly and efficiently infants encode sensory information, and with our child and adolescent studies demonstrating that (1) these neural measures change as a function of age, (2) underlying neural processes mature more slowly in individuals with neurodevelopmental disorders, and (3) in adolescents with autism spectrum disorder (ASD) these neural measures predict functional outcome. Examining brain structure and function in primary auditory, somatosensory, and visual cortical areas (115 infants recruited), we will show that development of fundamental sensory encoding processes is structurally constrained by mechanistic features: (1) age-related increases in white-matter maturation allowing faster neural signal propagation, and (2) age-related increases in gray-matter cortical thickness providing more active neural networks. Behavioral measures will also be obtained to allow exploration of associations between the most sensitive brain measures and behavior. It is our hope that via a longitudinal study we can identify brain biomarkers that predict future brain function, with use of these biomarkers in future studies to identify children at risk for neurodevelopmental disorders as well as to identify lines of therapeutic intervention and then finally to use the biomarkers to measure response to therapy.